Overview Datasets Severity Analysis Temporal Patterns Weather Impact Vehicle Analysis Casualty Analysis Key Findings

UK Traffic Accident Analysis (2015-2018)

Analysis Overview:

  • Total Accidents Analyzed: 529,294
  • Total Casualties: 699,163
  • Total Vehicles Involved: 975,680
  • Time Period: 2015-2018

Dataset Information

Accidents Dataset

Contains detailed information about each accident:

  • Accident_Index: Unique identifier for each accident
  • Date, Time: When the accident occurred
  • Location: Geographical coordinates and district information
  • Road_Type, Speed_limit: Road characteristics
  • Weather_Conditions, Light_Conditions: Environmental factors

Casualties Dataset

Details about individuals involved in accidents:

  • Casualty_Reference: Unique identifier for each casualty
  • Age_of_Casualty, Sex_of_Casualty: Demographic information
  • Casualty_Type: Type of road user (pedestrian, driver, etc.)
  • Casualty_Severity: Severity of injuries

Vehicles Dataset

Information about vehicles involved:

  • Vehicle_Reference: Unique identifier for each vehicle
  • Vehicle_Type: Category of vehicle
  • Age_of_Vehicle, Engine_Capacity_(CC): Vehicle characteristics
  • Age_of_Driver, Sex_of_Driver: Driver information

Accident Severity Analysis

Key Insights:

  • Overall decrease in accident numbers from 2015 to 2018
  • Slight accidents form the majority but show the steepest decline
  • Fatal accidents remain relatively stable despite overall reductions
  • Serious accidents show a slight upward trend in proportion

Temporal Patterns

Time of Day Analysis:

  • Peak accident times correlate with rush hours (8-9 AM and 5-6 PM)
  • Higher severity rates during nighttime hours
  • Lower accident frequency during early morning hours (2-5 AM)
  • Distinct patterns between weekdays and weekends

Age Distribution Analysis

Age-Related Findings:

  • Young adults (18-25) show higher involvement in accidents
  • Elderly casualties (65+) tend to have more severe injuries
  • Children under 15 show distinct casualty patterns
  • Middle-aged adults show the most varied severity distribution

Weather Impact Analysis

Weather-Related Insights:

  • Fine weather accounts for majority of accidents due to higher traffic volume
  • Rain increases accident likelihood but not necessarily severity
  • Snow and ice show fewer but more severe accidents
  • Fog and mist conditions show higher severity rates

Vehicle Type Analysis

Vehicle-Related Findings:

  • Cars dominate accident statistics due to their prevalence
  • Motorcycles show disproportionately high severity rates
  • Heavy vehicles (trucks, buses) show lower frequency but higher severity
  • Road type significantly influences accident severity for different vehicles

Casualty Demographics

Demographic Insights:

  • Gender disparities in accident involvement and severity
  • Age groups show different vulnerability patterns
  • Socio-economic factors influence casualty rates
  • Urban vs rural differences in casualty profiles

Key Findings and Recommendations

Major Trends

  • Overall accident rates show a declining trend (2015-2018)
  • Severity patterns vary significantly by time, location, and conditions
  • Demographic factors strongly influence accident outcomes
  • Environmental conditions play a crucial role in accident severity

Recommendations

  • Enhanced safety measures during peak hours
  • Targeted interventions for high-risk age groups
  • Weather-specific traffic management strategies
  • Vehicle-specific safety campaigns
  • Improved road design at high-risk locations

Future Research Directions

  • Deep dive into specific vehicle type patterns
  • Analysis of intervention effectiveness
  • Seasonal pattern investigation
  • Socio-economic factor analysis